高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

物联网双层耦合动力学信息传播模型研究

张月霞 常凤德

张月霞, 常凤德. 物联网双层耦合动力学信息传播模型研究[J]. 电子与信息学报, 2024, 46(8): 3165-3173. doi: 10.11999/JEIT231291
引用本文: 张月霞, 常凤德. 物联网双层耦合动力学信息传播模型研究[J]. 电子与信息学报, 2024, 46(8): 3165-3173. doi: 10.11999/JEIT231291
ZHANG Yuexia, CHANG Fengde. Research on the Double Layer Coupling Dynamic Information Propagation Model of the Internet of Things[J]. Journal of Electronics & Information Technology, 2024, 46(8): 3165-3173. doi: 10.11999/JEIT231291
Citation: ZHANG Yuexia, CHANG Fengde. Research on the Double Layer Coupling Dynamic Information Propagation Model of the Internet of Things[J]. Journal of Electronics & Information Technology, 2024, 46(8): 3165-3173. doi: 10.11999/JEIT231291

物联网双层耦合动力学信息传播模型研究

doi: 10.11999/JEIT231291 cstr: 32379.14.JEIT231291
详细信息
    作者简介:

    张月霞:女,教授,研究方向为无线协作通信技术等

    常凤德:男,硕士生,研究方向为复杂网络信息传播动力学模型

    通讯作者:

    张月霞 zhangyuexia@bistu.edu.cn

  • 中图分类号: TN929.5

Research on the Double Layer Coupling Dynamic Information Propagation Model of the Internet of Things

  • 摘要: 信息传播模型的研究是物联网领域的重要组成部分,它有助于提高物联网系统的性能和效率,促进物联网技术的进一步发展,针对物联网通信中影响信息传播的因素复杂且不稳定的问题,该文提出一种双层耦合信息传播模型SIVR-UAD,通过分析物联网中不同状态的设备和用户对信息传播的影响,建立了6种耦合状态,并利用马尔科夫方法分析耦合节点的状态变化过程,找到信息传播平衡点,最后通过理论分析证明了模型的平衡点的唯一性以及稳定性。仿真结果表明,在3组不同的初始耦合节点数下,SIVR-UAD模型中的6种耦合节点数量变化始终趋向同一稳定水平,证明了该模型的平衡点和稳定性。
  • 图  1  SIVR-UAD双层耦合信息传播模型

    图  2  不同状态的设备转换关系

    图  3  不同状态的用户转换关系

    图  4  设备用户耦合状态变换过程

    图  5  不同初始状态下SIVR-UAD模型演化

    图  6  不同系统参数下SIVR-UAD模型演化

    表  1  模型参数

    参数定义
    S未携带信息的设备
    I携带有效信息的设备
    V携带无效信息的设备
    R不再接收和传播信息的设备
    U不了解信息情况的用户
    A查看过信息且了解情况的用户
    D停止传播无效信息的用户
    $ {\beta _1} $单位时间设备S接收到有效信息的概率
    $ {\beta _2} $单位时间设备S接收到无效信息的概率
    $ {\mu _1} $单位时间设备I不再传播有效信息的概率
    $ {\mu _2} $单位时间设备V不再传播无效信息的概率
    $ \lambda $单位时间用户知道信息的概率
    $ \delta $单位时间用户不再传播无效信息的概率
    $ \varphi $单位时间设备R不再占用资源的概率
    下载: 导出CSV
  • [1] 徐瑶, 王玢. 物联网环境中的5G关键技术及产业化应用[J]. 数字通信世界, 2021(7): 53–54. doi: 10.3969/J.ISSN.1672-7274.2021.07.025.

    XU Yao and WANG Fen. 5G key technologies and industrialization application in internet of things environment[J]. Digital Communication World, 2021(7): 53–54. doi: 10.3969/J.ISSN.1672-7274.2021.07.025.
    [2] 宋晓虹. 物联网技术在智慧农业中的应用及发展模式创新探索[J]. 南方农机, 2022, 53(23): 163–165. doi: 10.3969/j.issn.1672-3872.2022.23.049.

    SONG Xiaohong. Exploration of the application and development model innovation of internet of things technology in smart agriculture[J]. Southern Agricultural Machinery, 2022, 53(23): 163–165. doi: 10.3969/j.issn.1672-3872.2022.23.049.
    [3] 王文斌. 城市综合管廊基于物联网融合通信系统应用分析[J]. 新型工业化, 2022, 12(9): 260–263. doi: 10.19335/j.cnki.2095-6649.2022.9.064.

    WANG Wenbin. Analysis of the application of integrated communication systems based on the internet of things in urban comprehensive pipe corridors[J]. The Journal of New Industrialization, 2022, 12(9): 260–263. doi: 10.19335/j.cnki.2095-6649.2022.9.064.
    [4] 陈章余. 物联网技术在电子通信领域的应用及其研究[J]. 信息与电脑, 2022, 34(12): 197–199. doi: 10.3969/j.issn.1003-9767.2022.12.062.

    CHEN Zhangyu. Application and research of internet of things technology in electronic communication[J]. Information & Computer, 2022, 34(12): 197–199. doi: 10.3969/j.issn.1003-9767.2022.12.062.
    [5] 闫思洁. 在物联网通信中应用计算机硬件及网络技术的实践途径[J]. 网络安全技术与应用, 2022(6): 31–33. doi: 10.3969/j.issn.1009-6833.2022.06.018.

    YAN Sijie. Practical approaches to applying computer hardware and network technology in IoT communication[J]. Network Security Technology & Application, 2022(6): 31–33. doi: 10.3969/j.issn.1009-6833.2022.06.018.
    [6] 杨青丰, 刘思雨, 唐丽萍. 5G网络下的物联网通信技术探讨[J]. 中国管理信息化, 2022, 25(9): 163–165.

    YANG Qingfeng, LIU Siyu, and TANG Liping. Exploration of IoT communication technology under 5G network[J]. China Management Informationization, 2022, 25(9): 163–165.
    [7] 贺英. 物联网通信服务平台保障系统的设计与实现研究[J]. 中国新通信, 2022, 24(17): 19–21.

    HE Ying. Research on the design and implementation of the internet of things communication service platform guarantee system[J]. China New Telecommunications, 2022, 24(17): 19–21.
    [8] 史国剑. 物联网技术在智慧交通中的应用分析[J]. 时代汽车, 2022(21): 193–195.

    SHI Guojian. Application analysis of internet of things technology in intelligent transportation[J]. Auto Time, 2022(21): 193–195.
    [9] 许晶晶. 人工智能与物联网在智慧城市中的应用研究[J]. 中国设备工程, 2023(4): 42–44. doi: 10.3969/j.issn.1671-0711.2023.04.019.

    XU Jingjing. Research on the application of artificial intelligence and the internet of things in smart cities[J]. China Plant Engineering, 2023(4): 42–44. doi: 10.3969/j.issn.1671-0711.2023.04.019.
    [10] 赵炬, 吴佩利, 孟然. 物联网在煤矿中的应用现状及展望[J]. 陕西煤炭, 2023, 42(1): 139–144. doi: 10.3969/j.issn.1671-749X.2023.01.030.

    ZHAO Ju, WU Peili, and MENG Ran. Application status and prospect of internet of things in coal mines[J]. Shaanxi Coal, 2023, 42(1): 139–144. doi: 10.3969/j.issn.1671-749X.2023.01.030.
    [11] 刘文孝, 李冰, 刘凯. 物联网技术在现代化农业发展中的应用[J]. 种子科技, 2023, 41(2): 123–125. doi: 10.19904/j.cnki.cn14-1160/s.2023.02.041.

    LIU Wenxiao, LI Bing, and LIU Kai. The application of internet of things technology in the development of modern agriculture[J]. Seed Science & Technology, 2023, 41(2): 123–125. doi: 10.19904/j.cnki.cn14-1160/s.2023.02.041.
    [12] 黄兴, 张文杰, 李曦, 等. 一种面向电力物联网的认知D2D网络能效资源分配算法[J]. 电测与仪表, 2023, 60(2): 97–103. doi: 10.19753/j.issn1001-1390.2023.02.014.

    HUANG Xing, ZHANG Wenjie, LI Xi, et al. Energy-efficient resource allocation algorithm for cognitive D2D networks for power IoT[J]. Electrical Measurement & Instrumentation, 2023, 60(2): 97–103. doi: 10.19753/j.issn1001-1390.2023.02.014.
    [13] 徐涵, 张庆. 复杂网络上传播动力学模型研究综述[J]. 情报科学, 2020, 38(10): 159–167. doi: 10.13833/j.issn.1007-7634.2020.10.024.

    XU Han and ZHANG Qing. A review of epidemic dynamics on complex networks[J]. Information Science, 2020, 38(10): 159–167. doi: 10.13833/j.issn.1007-7634.2020.10.024.
    [14] 王彦本. 传播动力学研究综述[J]. 通讯世界, 2015(3): 24. doi: 10.3969/j.issn.1006-4222.2015.03.017.

    WANG Yanben. Overview of communication dynamics research[J]. Telecom World, 2015(3): 24. doi: 10.3969/j.issn.1006-4222.2015.03.017.
    [15] 张鹏, 赵动员, 梅蕾. 移动社交网络信息传播研究述评与展望[J]. 情报科学, 2020, 38(2): 170–176. doi: 10.13833/j.issn.1007-7634.2020.02.025.

    ZHANG Peng, ZHAO Dongyuan, and MEI Lei. Review and prospect of information dissemination research on mobile social network[J]. Information Science, 2020, 38(2): 170–176. doi: 10.13833/j.issn.1007-7634.2020.02.025.
    [16] 汪意. 基于SEIR模型的复杂网络上的疾病传播动力学与隔离措施研究[D]. [硕士论文], 杭州师范大学, 2021. doi: 10.27076/d.cnki.ghzsc.2021.000728.

    WANG Yi. Research on dynamics of disease spreading and isolation measures in complex networks based on SEIR model[D]. [Master dissertation], Hangzhou Normal University, 2021. doi: 10.27076/d.cnki.ghzsc.2021.000728.
    [17] 许云霞, 雷学红. 具有Logistic增长的SIRS传染病模型的稳定性及最优控制分析[J]. 湖北民族大学学报: 自然科学版, 2020, 38(2): 200–205. doi: 10.13501/j.cnki.42-1908/n.2020.06.017.

    XU Yunxia and LEI Xuehong. Dynamic analysis and optimal control of an SIRS epidemic model with logistic growth[J]. Journal of Hubei Minzu University: Natural Science Edition, 2020, 38(2): 200–205. doi: 10.13501/j.cnki.42-1908/n.2020.06.017.
    [18] 张倩. 基于帕累托原理和节点地位的社交网络信息传播模型与控制方法[D]. [硕士论文], 西华大学, 2021. doi: 10.27411/d.cnki.gscgc.2021.000323.

    ZHANG Qian. Social network information dissemination models and control methods based on Pareto principle and node status[D]. [Master dissertation], Xihua University, 2021. doi: 10.27411/d.cnki.gscgc.2021.000323.
    [19] 崔雪莲, 那日萨. 基于消费者信任关系的在线口碑信息传播模型[J]. 系统管理学报, 2020, 29(3): 1090–1100. doi: 10.3969/j.issn1005-2542.2020.06.007.

    CUI Xuelian and Narisa. Modeling of online word-of-mouth information diffusion based on consumer trust relationship[J]. Journal of Systems & Management, 2020, 29(3): 1090–1100. doi: 10.3969/j.issn1005-2542.2020.06.007.
    [20] 沈庆磊, 邓月. 基于复杂网络的微商信息传播模型研究[J]. 模糊系统与数学, 2022, 36(2): 145–154.

    SHEN Qinglei and DENG Yue. Research on wechat information transmission model based on complex network[J]. Fuzzy Systems and Mathematics, 2022, 36(2): 145–154.
    [21] 王志双. 双层耦合网络上的传播行为与扩散动力学研究[D]. [博士论文], 天津理工大学, 2021. doi: 10.27360/d.cnki.gtlgy.2021.000825.

    WANG Zhishuang. Propagation behavior and diffusion dynamics in two-layered coupling networks[D]. [Ph. D. dissertation], Tianjin University of Technology, 2021. doi: 10.27360/d.cnki.gtlgy.2021.000825.
    [22] 王欢. 双层网络上的传播动力学建模及分析[D]. [硕士论文], 安徽大学, 2020. doi: 10.26917/d.cnki.ganhu.2020.001180.

    WANG Huan. Modeling and analysis of the spreading dynamics in two-layer multiplex networks[D]. [Master dissertation], Anhui University, 2020. doi: 10.26917/d.cnki.ganhu.2020.001180.
    [23] SCATÀ M, DI STEFANO A, LA CORTE A, et al. A multiplex social contagion dynamics model to shape and discriminate D2D content dissemination[J]. IEEE Transactions on Cognitive Communications and Networking, 2021, 7(2): 581–593. doi: 10.1109/TCCN.2020.3027697.
    [24] SCATÀ M, DI STEFANO A, LA CORTE A, et al. Quantifying the propagation of distress and mental disorders in social networks[J]. Scientific Reports, 2018, 8(1): 5005. doi: 10.1038/s41598-018-23260-2.
    [25] RAHMEDE C, IACOVACCI J, ARENAS A, et al. Centralities of nodes and influences of layers in large multiplex networks[J]. Journal of Complex Networks, 2018, 6(5): 733–752. doi: 10.1093/comnet/cnx050.
    [26] ZHANG Zufan, LIU Anqi, YI Yinxue, et al. Exploring the dynamical behavior of information diffusion in D2D communication environment[J]. Security and Communication Networks, 2020, 2020: 8848576. doi: 10.1155/2020/8848576.
    [27] SANG Chunyan and LIAO Shigen. Modeling and simulation of information dissemination model considering user’s awareness behavior in mobile social networks[J]. Physica A: Statistical Mechanics and Its Applications, 2020, 537: 122639. doi: 10.1016/j.physa.2019.122639.
    [28] 杨云鹏, 樊重俊, 杨坚争, 等. 基于官方信息控制的多层网络谣言传播模型[J]. 计算机应用研究, 2018, 35(5): 1294–1297, 1314. doi: 10.3969/j.issn.1001-3695.2018.05.003.

    YANG Yunpeng, FAN Chongjun, YANG Jianzheng, et al. Rumor propagation model on multilayered interconnected complex networks based on official information driven[J]. Application Research of Computers, 2018, 35(5): 1294–1297, 1314. doi: 10.3969/j.issn.1001-3695.2018.05.003.
    [29] 罗章凯, 裴忠民, 熊伟, 等. 双层均质耦合网络信息传播动力学研究[J]. 计算机仿真, 2023, 40(1): 43–47. doi: 10.3969/j.issn.1006-9348.2023.01.009.

    LUO Zhangkai, PEI Zhongmin, XIONG Wei, et al. Research on dynamics of information spreading on double-layer coupled networks[J]. Computer Simulation, 2023, 40(1): 43–47. doi: 10.3969/j.issn.1006-9348.2023.01.009.
    [30] 朱恒民, 杨柳, 马静, 等. 基于耦合网络的线上线下互动舆情传播模型研究[J]. 情报杂志, 2016, 35(2): 139–144,150. doi: 10.3969/j.issn.1002-1965.2016.02.025.

    ZHU Hengmin, YANG Liu, MA Jing, et al. Study on public opinion propagation model based on coupled networks under onlineto offline interaction[J]. Journal of Intelligence, 2016, 35(2): 139–144,150. doi: 10.3969/j.issn.1002-1965.2016.02.025.
    [31] 魏静, 黄阳江豪, 朱恒民. 基于耦合网络的社交网络舆情传播模型研究[J]. 现代情报, 2019, 39(10): 110–118. doi: 10.3969/j.issn.1008-0821.2019.10.013.

    WEI Jing, HUANG Yangjianghao, and ZHU Hengmin. Research on public opinion communication model of social network based on coupling network[J]. Journal of Modern Information, 2019, 39(10): 110–118. doi: 10.3969/j.issn.1008-0821.2019.10.013.
    [32] 甘臣权, 刘安棋, 张祖凡, 等. D2D通信中用户意识与信息耦合传播建模分析[J]. 电子与信息学报, 2022, 44(8): 2767–2776. doi: 10.11999/JEIT210535.

    GAN Chenquan, LIU Anqi, ZHANG Zufan, et al. Modeling and analysis of user awareness and information coupling propagation in D2D communications[J]. Journal of Electronics & Information Technology, 2022, 44(8): 2767–2776. doi: 10.11999/JEIT210535.
    [33] 张欣欣, 许力, 徐振宇. 基于网络模体的移动社会网络信息可控传播方法[J]. 电子与信息学报, 2023, 45(2): 635–643. doi: 10.11999/JEIT211429.

    ZHANG Xinxin, XU Li, and XU Zhenyu. Information propagation control method in mobile social networks based on network motifs[J]. Journal of Electronics & Information Technology, 2023, 45(2): 635–643. doi: 10.11999/JEIT211429.
    [34] LI Wenyao, CAI Meng, ZHONG Xiaoni, et al. Coevolution of epidemic and infodemic on higher-order networks[J]. Chaos, Solitons & Fractals, 2023, 168: 113102. doi: 10.1016/J.CHAOS.2023.113102.
    [35] NIE Yanyi, LI Wenyao, PAN Liming, et al. Markovian approach to tackle competing pathogens in simplicial complex[J]. Applied Mathematics and Computation, 2022, 417: 126773. doi: 10.1016/j.amc.2021.126773.
  • 加载中
图(6) / 表(1)
计量
  • 文章访问数:  164
  • HTML全文浏览量:  93
  • PDF下载量:  25
  • 被引次数: 0
出版历程
  • 收稿日期:  2023-11-21
  • 修回日期:  2024-04-14
  • 网络出版日期:  2024-05-11
  • 刊出日期:  2024-08-30

目录

    /

    返回文章
    返回